Introduction to Data Mining and its Applications
This book explores the concepts of data mining and data warehousing, a promising and flourishing frontier in data base systems and new data base applications and is also designed to give a broad, yet in-depth overview of the field of data mining. Data mining is a multidisciplinary field, drawing work from areas including database technology, AI, machine learning, NN, statistics, pattern recognition, knowledge based systems, knowledge acquisition, information retrieval, high performance computing and data visualization.
Information Systems Reengineering and Integration
This text takes a practical approach to re-engineering existing systems and looks at data integration, and focuses on proven methods and tools for: •the conversion of hierarchical or network database systems into relational database technology, or from relational to object-oriented and XML databases •the integration of database systems and expert systems to produce MIS and EIS systems Taking a very practical approach, the book describes in detail database conversion techniques, reverse engineering and forward engineering, and re-engineering methodology for information systems, offering a systematic software engineering approach for reusing existing database systems built with "old" technology. Many examples, illustrations and case studies are used, making the methodology easy to follow.
Enterprise Information Systems VII
The purpose of the 7th International Conference on Enterprise Information Systems (ICEIS) was to bring together researchers, engineers and practitioners interested in the advances and business applications of information systems. Five simultaneous tracks have been held, covering different aspects of Enterprise Information Systems Applications, including Enterprise Database Technology, Systems Integration, Artificial Intelligence, Decision Support Systems, Information Systems Analysis and Specification, Internet Computing, Electronic Commerce and Human Factors.
Database theory - ICDT 2005 ; 10th international conference, Edinburgh, UK, January 5-7, 2005, Proceedings
This volume collects the papers presented at the 10th International Conference on Database Theory, ICDT 2005, held during January 5–7, 2005, in Edinburgh, UK. ICDT (http://alpha.luc.ac.be/~lucp1080/icdt/) has now a long tra- tion of international conferences, providing a biennial scienti?c forum for the communication of high-quality and innovative research results on theoretical - pects of all forms of database systems and database technology. The conference usually takes place in Europe, and has been held in Rome (1986), Bruges (1988), Paris (1990), Berlin (1992), Prague (1995), Delphi (1997), Jerusalem (1999), London (2001), and Siena (2003) so far. ICDT has merged with the Sym- sium on Mathematical Fundamentals of Database Systems (MFDBS), initiated in Dresden in 1987, and continued in Visegrad in 1989 and Rostock in 1991. ICDT had a two-stage submission process. First, 103 abstracts were subm- ted, which were followed a week later by 84 paper submissions. From these 84 submissions, the ICDT Program Committee selected 24 papers for presentation at the conference. Most of these papers were “extended abstracts” and preli- nary reports on work in progress. It is anticipated that most of these papers will appear in a more polished form in scienti?c journals.
Database and XMLTechnologies ; 5th International XML Database Symposium, XSym 2007, Vienna, Austria, September 23-24, 2007, Proceedings
This book discuss the use of and synergy between databases and XML. It provided theory and practice of XML data management and its applications. This volume also contains current research in XPath and XQuery processing, XML Updates, Temporal XML and Constraints.
Database and XML Technologies ; Vol. 4156 ; 4th International XML Database Symposium, XSym 2006, Seoul, Korea, September 10-11, 2006, Proceedings
The theme of the XML Database Symposium (XSym) is the convergence of database technology with XML technology. Since the first International XML Symposium in 2003, XSym has continued to provide a forum for academics, practitioners, users and vendors to discuss the use of and synergy between advanced XML technologies. XSym 2006 received 32 full paper submissions. Each submitted paper underwent a rigorous review by independent referees. These proceedings represent a collection of eight excellent research papers. Their focus is on building XML repositories and covers the following topics: XML query processing, caching, indexing and navigation support, structural matching, temporal XML, and XML updates.
Data Management. Data, Data Everywhere ; 24th British National Conference on Databases, BNCOD 24, Glasgow, UK, July 3-5, 2007, Proceedings
One of the most pressing challenges is to ?nd ways of evolving database technology to cope with its new role in underpinning the massively distributed and heterogeneous applications built on top of the Internet. This has afiected both the ways in which data has been accessed and the ways in which it is represented, with XML data management becoming an important issue and, as such, heavily represented at this conference. It has also brought back issues of performance that might have been considered largely solved by the improvements in hardware, since data now has to be managed on devices of low power and small memory as well as on standard client and powerful server machines. We therefore invited papers on all aspects of data management, particularly related to how dataisused in the ubiquitous environment of the modern Internet by complex distributed and scientific applications.
Current trends in database technology - EDBT 2006 ; EDBT 2006 Workshop PhD, DataX, IIDB, IIHA, ICSNW, QLQP, PIM, PaRMa, and Reactivity on the Web, Munich, Germany, March 26-31, 2006, Revised Selected Papers
This book constitutes the thoroughly refereed joint post-proceedings of nine workshops held as part of the 10th International Conference on Extending Database Technology, EDBT 2006, held in Munich, Germany in March 2006. The 70 revised full papers presented were selected from numerous submissions during two rounds of reviewing and revision.
Current trends in database technology - EDBT 2004 Workshops ; EDBT 2004 Workshops PhD, DataX, PIM, P2P&DB, and ClustWeb, Heraklion, Crete, Greece, March 14-18, 2004, Revised Selected Papers
This volume comprises papers from the following ?ve workshops that were part of the complete program for the International Conference on Extending Database Technology (EDBT) held in Heraklion, Greece, March 2004: • ICDE/EDBT Joint Ph. D. Workshop (PhD) • Database Technologies for Handling XML-information on the Web (DataX) • Pervasive Information Management (PIM) • Peer-to-Peer Computing and Databases (P2P&DB) • Clustering Information Over the Web (ClustWeb) Together, the ?ve workshops featured 61 high-quality papers selected from appr- imately 180 submissions.
Local Pattern Detection ; International Seminar Dagstuhl Castle, Germany, April 12-16, 2004, Revised Selected Papers
Introduction The dramatic increase in available computer storage capacity over the last 10 years has led to the creation of very large databases of scienti?c and commercial information. The need to analyze these masses of data has led to the evolution of the new field knowledge discovery in databases (KDD) at the intersection of machine learning, statistics and database technology. Being interdisciplinary by nature, the field offers the opportunity to combine the expertise of different fields into a common objective. Moreover, within each field diverse methods have been developed and justified with respect to different quality criteria. We have to investigate how these methods can contributet o solving the problem of KDD. Traditionally, KDD was seeking to end global models for the data that - plain most of the instances of the database and describe the general structure of the data. Examples are statistical time series models, cluster models, logic programs with high coverageor classi?cation models like decision trees or linear decision functions. In practice, though, the use of these models often is very l- ited, because global models tend to end only the obvious patterns in the data, 1 which domain experts already are aware of . What is really of interest to the users are the local patterns that deviate from the already-known background knowledge. David Hand, who organized a workshop in 2002, proposed the new field of local patterns.
Knowledge Discovery in Inductive Databases ; Vol.3933 ; 4th International Workshop, KDID 2005, Porto, Portugal, October 3, 2005, Revised Selected and Invited Papers
The 4th International Workshop on Knowledge Discovery in Inductive Databases (KDID 2005) was held in Porto, Portugal, on October 3, 2005 in conjunction with the 16th European Conference on Machine Learning and the 9th European Conference on Principles and Practice of Knowledge Discovery in Databases. Ever since the start of the ?eld of data mining, it has been realized that the integration of the database technology into knowledge discovery processes was a crucial issue. This vision has been formalized into the inductive database perspective introduced by T. Imielinski and H. Mannila (CACM 1996, 39(11)). The main idea is to consider knowledge discovery as an extended querying p- cess for which relevant query languages are to be speci?ed.
Knowledge Discovery in Inductive Databases ; 5th International Workshop, KDID 2006 Berlin, Germany, September 18th, 2006 Revised Selected and Invited Papers
Constitutes the thoroughly refereed joint postproceedings of the 5th International Workshop on Knowledge Discovery in Inductive Databases, KDID 2006. The papers address various current topics in knowledge discovery and data mining in the framework of inductive databases such as constraint-based mining, database technology and inductive querying.
Beginning C# 2008 Databases : From novice to professional
Assuming only basic knowledge of C# 2008, Beginning C# 2008 Databases teaches all the fundamentals of database technology and database programming readers need to quickly become highly proficient database users and application developers. A comprehensive tutorial on both SQL Server 2005 and ADO.NET 3.0, Beginning C# 2008 Databases explains and demonstrates how to create database objects and program against them in both T–SQL and C#. Full of practical, detailed examples, it's been fully revised and updated for C# 2008 and offers the most complete, detailed, and gentle introduction to database technology for all C# programmers at any level of experience.
Advances in database technology -- EDBT 2006 ; 10 International conference on extending database technology, Munich, Germany, 26-31 March 2006, Proceedings
The series of International Conferences on Extending Database Technology (EDBT) is an established and prestigious forum for the exchange of the latest research results in data management. It provides unique opportunities for database researchers, practitioners, developers, and users to explore new ideas, techniques, and tools, and to exchange experiences. This volume contains the proceedings of the 10th EDBT Conference, held in Munich, Germany, March 27-29, 2006. The conference included 3 keynote talks, 56 full-size and 4 half-size research papers in 20 sessions, 8 industrial presentations in 3 sessions, 1 panel session, 5 tutorials in 7 sessions, and 20 demonstrations in 4 sessions. All of the research papers as well as papers and abstracts from most of the other sessions are included here.
Advanced Techniques in Knowledge Discovery and Data Mining
This explosion is a result of the growing use of electronic media. But what is data mining (DM)? A Web search using the Google search engine retrieves many (really many) definitions of data mining. We include here a few interesting ones. One of the simpler definitions is: “As the term suggests, data mining is the analysis of data to establish relationships and identify patterns” [1]. It focuses on identifying relations in data. Our next example is more elaborate: An information extraction activity whose goal is to discover hidden facts contained in databases. Using a combination of machine learning, statistical analysis, modeling techniques and database technology, data mining finds patterns and subtle relationships in data and infers rules that allow the prediction of future results. Typical applications include market segmentation, customer profiling, fraud detection, evaluation of retail promotions, and credit risk analysis .














